Given current advances in imaging devices and computer processing power, volumetric datasets are produced in numerous different applications. For example, more and more present-day imaging systems such as Magnetic Resonance Imagers (MRI) or Computed Tomography (CT) produce volumetric datasets providing a clinical practitioner with substantially more information by allowing viewing of an imaged region of a patient's body from various viewing directions. Furthermore, various fields such as meteorology, geophysics, astrophysics, and engineering benefit these days from measurements and computer simulations producing volumetric datasets.
However, visualization of the volumetric datasets presents specific challenges not found in representations of two dimensional data. In 2D representations all information is restricted to a plane perpendicular to a view point. The addition of the third dimension allows objects to be interposed between the view point and other objects in a scene. Therefore, the preservation of spatial relationships is important in constructing a physically plausible scene or, in other words, the detail of the scene needs to be maintained in the context in which it exists.
Increasing availability of powerful workstations has fueled the development of new methods for visualizing a volumetric dataset—commonly represented by a 3D grid of volume elements or voxels. The process of presenting a volumetric dataset from a given viewpoint is commonly referred to as volume rendering, and is one of the most common techniques for visualizing a 3D object or phenomenon represented by voxels at the grid points of the volumetric dataset.
Various applications often require effective and fast visualization of internal features of a volumetric dataset. In a clinical application, for instance, rapid determination of size, shape, and spatial location of a lesion can be life-saving in emergency situations. To this end, clinicians need to have quick close-up visualization of the data from multiple viewing directions in high-quality images of a specific internal Region Of Interest (ROI), while preserving overall contextual and spatial information.
Present multi-resolution techniques for volume rendering are based on a brick data structure to allow various levels of detail, as disclosed, for example, in LaMar E., Hamann B., Joy K.: “Multiresolution techniques for interactive texture-based volume visualization”, Proc. IEEE Visualization '99 (1999), pp. 355-543; in Weiler M., Westermann R., Hansen C., Zimmermann K., Ertl T.: “Level-of detail volume rendering via 3D textures”, Proc. IEEE Volume Visualization and Graphic Symposium '00 (2000); and in Wang C., Shen H.-W.: “Hierarchical navigation interface: Leveraging multiple coordinated views for level-of-detail multiresolution volume rendering of large scientific datasets”, Proc. of International Conference on Information Visualization '05 (2005). Unfortunately, these techniques require processing of large data volumes during user interactivity, for example, for selecting a ROI or changing a viewing direction, resulting in a slow response of the processing system and, consequently, making the viewing of a large volumetric dataset an arduous task.
Existing techniques for direct volume rendering also suffer from the problem of occlusion by exterior 1features. Transfer functions, clipping, or segmentation have been applied to alleviate this problem, as disclosed, for example, in Bruckner S., Grimm S., Kanitsar A., Gröller M. E.: “Illustrative context-preserving volume rendering”, Proc. of EuroVis 2005 (2005), pp. 69-76. However, these techniques typically obscure details in the final image with overlapping structures and remove important contextual information.
It would be highly desirable to overcome the drawbacks of the present techniques by providing fast high resolution close-up visualization of a ROI for use with off-the-shelf Graphics Processing Units (GPU) on a personal computer or workstation. It would be further highly beneficial to provide a contextual close-up visualization of a ROI without obscuring details.